Biostatistics involves the designing and conducting of statistical research on subject matter within the biological disciplines. Biostatistics, also referred to as biometrics combines statistical techniques with biological concepts and realities in identifying, describing, analysing social and scientific problems. Biostatistics is strongly associated with medical and pharmaceutical research despite the discipline involving any facets of biology including fauna and flora.
Biostatistics, as a quantitative research concern, requires the use of highly precise methodologies that enhance the accuracy of tests and conclusions. For instance biostatistics is used in precision-demanding research such as:
- Testing the effects of a cure or treatment on candidates
- Studying the relationships between diseases and conditions with external factors including geography, occupation, etc.
- Identifying relationships between symptoms and suspected causes
- Understanding and developing models for the spread of infections
- Understanding biological risks that communities are exposed to
- Getting accurate prevalence rates of diseases, infections, etc.
Thus, issues of validity and reliability take centre stage in biological research because of the implications of the conclusions made from this type of research. Poorly designed studies can result in inappropriate sampling strategies, data collection and analysis threatening the reliability of results and in cases resulting in the generation of erroneous conclusions and recommendation putting lives at risks on top of wasting scarce resources.
Types of studies in biostatistics
Biostatistics exists within the quantitative research realm and under its several types of studies can be noted:
- Experiments: tests that involve administering a treatment or condition to a test group to test the effects thereof. A comparison between the treatment candidates and the control groups is used to conclude whether the treatment and condition had the hypothesized effect on candidates. Experiments are, without much doubt, the most reliable types of studies in human health sciences.
- Quasi-experiments: These are like experiments but differ in that they do not use control groups.
- Clinical trials: clinical trials are experiments and quasi-experiments were the effects of a medical or pharmaceutical intervention are tested on real life cases.
- Surveys, interviews: data is collected from candidates who are believed to be able to provide answers that can better the understanding of a phenomenon of interest
- Records analysis: medical facilities record information on patients and this information can be ethically used to analyse phenomenon of interest. For example we could use hospital records to investigate the relationship between age and the prevalence of sexually-transmitted illnesses within a certain community.
- Comparative studies: These compare variables between two or more cases with the view that identified differences and similarities can help to understand a phenomenon of interest. For example, one might compare the dietary composition of candidates who suffer from peptic ulcers and those who do not.
- Document research: This involves the analysis of already existing documents and sources in an attempt to answer research questions of interest.
The above studies generate volumes of data that must be reliably analysed and interpreted. However, for this to be possible, the whole research designing process must have been done with integrity. Biostatics is not well-associated with qualitative studies. However, it is not uncommon to use qualitative research to augment and consolidate our understanding of health phenomenon. Qualitative studies are, therefore, important in complementing biostatistical research.